A more recent publication of this set of statistics is available.
Latest publication: Labour force survey 2019, July
Quality Description: Labour force survey
 1. Relevance of statistical information
 2. Methodological description of the statistical survey
 3. Correctness and accuracy of data
 4. Timeliness and promptness of published data
 5. Accessibility and transparency/clarity of data
 6. Comparability of statistics
 7. Coherence and consistency/uniformity
1. Relevance of statistical information
The Labour Force Survey is a sample survey providing monthly, quarterly and annual statistics on participation in the labour market, employment, unemployment and working hours among the population aged between 15 and 74. Approximately 12,000 persons are interviewed each month about their labour market activities during one week. Based on the information given by the respondents, the survey provides an uptodate and comprehensive picture of the labour force and changes in the labour market.
The results of the survey are used, inter alia, in preparing labour market projections and plans, as support for decisionmaking and in the followup of the employment effects of different measures. Key users of the results are ministries, authorities responsible for regional planning, employers’ and employees’ organisations, universities and research institutions, international organisations and the European Union. Statistics Finland uses the data, inter alia, in the compilation of the National Accounts. Public attention focuses each month especially on the changes in unemployment and employment from the corresponding month in the previous year.
The current data content of the Labour Force Survey is based mainly on the EU Regulation on the organisation of a labour force sample survey in the Community (Council Regulation No 577/98). More detailed information on the European Union Labour Force Survey is available at http://circa.europa.eu/irc/dsis/employment/info/data/eu_lfs/index.htm.
The Labour Force Survey mainly describes persons. Since 2003, information is obtained from a sub sample also on the structure of households and the activities of all workingage members of a household with regard to the labour market. Since 1999 a unified EU ad hoc survey with annually changing topics has been conducted in connection with the Labour Force Survey.
The concepts and definitions used in the survey follow the recommendations of ILO, the International Labour Organisation of the UN, and the regulations of Eurostat, the Statistical Office of the European Communities. In the basic classification of the labour market situation, the population is divided into the employed, the unemployed and the economically inactive.
Definitions:

A person is employed if he/she has during the survey week been in gainful employment at least one hour against wages or salary or fringe benefits, or to make profit. Persons temporarily absent from work due to e.g. holiday or illness are classified as employed. Persons laid off for a fixedterm (less than 3 months) as well as persons on maternity, paternity or parental leave from work are classified as employed. Other persons absent without pay from work for over one month (e.g. conscripts, persons receiving home care subsidies while looking after a child or on job alternation leave or leave of absence) are not classified as employed. The employed are divided into wage and salary earners, entrepreneurs and unpaid workers in a family member's enterprise.

A person is unemployed if he/she is without work during the survey week, has actively sought employment in the past four weeks as a wage or salary earner or entrepreneur and would be available for work within two weeks. A person who is without work and waiting for an agreed job to start within two weeks is also classified as unemployed. Persons laid off for the time being who fulfil the abovementioned criteria on job seeking and availability for work are also classified as unemployed.

The labour force comprises all persons aged between 15 and 74 who are employed or unemployed during the survey week.

The economically inactive population consists of persons who are not employed or unemployed during the survey week. The economically inactive can be divided according to principal activity during the survey week into students, conscripts, persons performing domestic work, persons retired on account of age or work years, the disabled, persons living on interest or capital income as well as others not included in the abovementioned classes.
Statistical classifications used in the Labour Force Survey include the Standard Industrial Classification (TOL 2002, ISIC REV 3.1), the Classification of Occupations 2001 (ISCO88) and the Classification of Occupations 1987, the Classification of Socioeconomic Groups 1989, the Classification of Education 1997 (ISCED 1997) as well as the regional classifications Major Region (NUTS2), Province, Employment and Economic Development Centre and Region.
2. Methodological description of the statistical survey
The population of the Labour Force Survey consists of persons aged between 15 and 74 who are permanent residents of Finland. The population includes also persons residing abroad temporarily (less than a year) as well as foreign nationals registered in the Finnish Population Information System who will reside in Finland at least one year. Information is delivered to Eurostat, the Statistical Office of the European Communities, also on persons younger than 15 and aged 75 or older (who are not interviewed). In the survey, age is determined on the basis of real age at the time of the interview. Hence a 14yearold can belong to the sample but is included only after he/she has turned 15. Correspondingly the most aged persons are left out of the survey when they turn 75.
The sample of the Labour Force Survey is drawn twice a year as a stratified random sample from the Statistics Finland population database, which is based on the central population register. The survey is a panel survey in which one person is interviewed five times. The interviews are conducted every three months apart from the fourth interview, which is conducted six months after the third interview. The first and last interviews are 15 months apart. The sample in each month consists approximately of 12,000 persons, which is, on average, every 300th person from the population. The sample consists of five rotation groups which have joined the survey in different months. The sample changes gradually so that different persons answer the questions during three consecutive months. In consecutive quarters threefifths of the respondents are the same. In consecutive years the overlap is two fifths.
Statistics Finland’s interviewers collect the data with computerassisted telephone interviews. In 2006 approximately 116,000 interviews were conducted of which 99 per cent were telephone interviews and 1 per cent facetoface interviews. The nonresponse rate of the survey was 19.6 per cent on average, 21.0 per cent for men and 18.2 per cent for women.
The results from the sample are weighted to correspond to the entire population aged between 15 and 74. The effects of nonresponse on the results are corrected by using so called weight calibration, in which weighting is used to produce the correct population distributions by region, gender and age. Information of the Ministry of Labour’s job seeker register is also used as supplementary data.
The figures published in the Labour Force Survey, as figures collected with any sample survey, are socalled estimates. An estimate is an estimation of a quality of the population derived by applying a mathematical operation (estimation) to sample observations. For example, the number of the unemployed in 2005, which was 249,000 persons, is an estimate of the number of unemployed persons aged between 15 and 74 resulting from such a procedure.
Quarterly and annual estimates are averages of monthly estimates. Working days and working hours are estimated on the basis of the number of calendar days in the relevant month. Quarterly and annual estimates of working days and working hours are sums of monthly estimates.
The employment and unemployment numbers in the Labour Force Survey vary relatively regularly in different months of the year. Variation which occurs annually in similar ways has been removed from the socalled trends which are also published from the Labour Force Survey. The direction of longterm developments and cyclical variations are easier to see from a trend than from unadjusted monthly data. Due to the method used, the last data of the trend are revised somewhat when the data of the following month are inserted into the series. This preliminary nature of trends must be taken into account when drawing conclusions. As from June 2007, the trend components of the time series are calculated with the Tramo/Seats method recommended by Eurostat, the Statistical Office of the European Communities.
3. Correctness and accuracy of data
The reliability of the estimates of the Labour Force Survey is affected by nonresponse (see above), measurement error and random variation due to sampling.
Measurement errors arise, inter alia, due to the fact that questions can be understood or interpreted differently and respondents may not report some information. Developing the questionnaire and training the interviewers are measures used to contain measurement errors.
Random variation due to sampling means that figures calculated from different samples differ somewhat from each other. When evaluating roughly the magnitude of random variation due to sampling in different situations, the main principle is that 1) the larger the sample is from which the figures are calculated and 2) the larger the population described by the figures is, the less uncertainty due to sampling there will be in the figures. For instance, quarterly figures are more accurate than monthly figures describing the same phenomenon, as quarterly data have been collected by interviewing thrice the number of persons than the monthly data. Annual figures are the most accurate. The second principle means that the figures of the employed and the unemployed, that is the estimates, based on a sample of the same size are the more accurate the larger the subgroup they apply to. As the relevant subgroup becomes smaller, random variation due to sampling increases. Therefore e.g. the numbers of the unemployed in different age groups or in different regions are not as reliable as the number of all the unemployed.
Inaccuracy due to sampling is assessed with the standard error of the estimate. The magnitude of the standard error is influenced by the size of the sample and the variance of the variable being investigated. Standard error can be used to calculate the confidence interval, within which the value of the population lies with a certain probability. The 95 per cent confidence interval used in the Labour Force Survey is the interval within which the real value of the property being investigated lies with a probability of 95 per cent. For example, the confidence interval of the number of the unemployed in January 2005 is 249,000 ± 16,000, i.e. 233,000–265,000. The share to be added to the estimate or deducted from it, in this case 16,000, is obtained by multiplying the estimate’s standard error, here 8,000 persons, with the coefficient of the 95 per cent confidence interval.
Examples of the accuracy of the number of the employed and the unemployed by size of subgroup
To illustrate the magnitude of random variation, examples of the estimates of different numbers of the employed and the unemployed, their 95 per cent confidence intervals and other key figures of reliability are presented in the following tables 13. The magnitude of random variation in the examples is a rough estimate of the upper boundary of random variation, when the figure being investigated is a correspondingly large estimate of the number of the employed or the unemployed by gender, age or region. In correspondingly large subgroups by industry, the confidence interval is wider. The examples in table 1 refer to monthly estimates. Tables 23 include the corresponding data for quarterly and annual estimates.
Table 1. Examples of the accuracy of monthly estimates of different sizes: the numbers of the employed and the unemployed by gender, age and region.^{1)}
Monthly estimate  Monthly estimate's 95% confidence interval 
Standard error  Relative standard error 

persons  persons  persons  %  
Employed  2 400 000  ± 27 800  14 200  0,6 
1 200 000  ± 21 000  10 700  0,9  
600 000  ± 15 300  7 800  1,3  
300 000  ± 11 600  5 900  2,0  
100 000  ± 6 700  3 400  3,4  
50 000  ± 4 700  2 400  4,8  
10 000  ± 2 900  1 500  15,0  
Unemployed  230 000  ± 15 100  7 700  3,3 
120 000  ± 11 800  6 000  5,0  
90 000  ± 10 800  5 500  6,1  
60 000  ± 9 000  4 600  7,7  
30 000  ± 6 900  3 500  11,7  
20 000  ± 5 100  2 600  13,0  
10 000  ± 3 700  1 900  19,0 
1) The data can be used as indicative estimates of the accuracy of comparable numbers of the employed and unemployed by gender, are and region.
We can see from table 1 that if the monthly estimate of the employed in the subgroup is 300,000 persons, the real number of the employed lies, with a probability of 95 per cent, within the range 300,000 ± 11,600 persons. The size of this confidence interval relative to the size of the estimate is clearly larger than the corresponding share in the large estimate on the first row of the table. For estimates of less than 300,000 persons the confidence intervals are relatively even wider.
A comparison of data in tables 1–3 illustrates also that annual and quarterly data are more accurate than monthly data. The 95 per cent confidence interval corresponding to the estimate of the employed in a subgroup of 300,000 persons examined above, that is 300,000 ± 6,700 persons (table 2), is clearly narrower than the confidence interval of the monthly estimate. Annual estimated are even more accurate than quarterly estimates (table 3). This difference in accuracy is, however, not as large as the corresponding difference between monthly and quarterly data.
Table 2. Examples of the accuracy of quarterly estimates of different sizes: the numbers of the employed and the unemployed by gender, age and region.^{1)}
Quarterly estimate  Quarterly estimate's 95% confidence interval 
Standard error  Relative standard error 

persons  persons  persons  %  
Employed  2 400 000  ± 16 100  8 200  0,3 
1 200 000  ± 12 500  6 400  0,5  
600 000  ± 8 800  4 500  0,8  
300 000  ± 6 700  3 400  1,1  
100 000  ± 4 700  2 400  2,4  
50 000  ± 3 900  2 000  4,0  
10 000  ± 2 000  1 000  10,0  
Unemployed  230 000  ± 8 800  4 500  2,0 
120 000  ± 6 900  3 500  2,9  
90 000  ± 6 100  3 100  3,4  
60 000  ± 5 100  2 600  4,3  
30 000  ± 3 500  1 800  6,0  
20 000  ± 3 100  1 600  8,0  
10 000  ± 2 400  1 200  12,0 
1) The data can be used as indicative estimates of the accuracy of comparable numbers of the employed and unemployed by gender, are and region.
Table 3. Examples of the accuracy of annual estimates of different sizes: the numbers of the employed and the unemployed by gender, age and region.^{1)}
Annual estimate 
Annual estimate's 95% confidence interval 
Standard error  Relative standard error 

persons  persons  persons  %  
Employed  2 400 000  ± 15 700  8 000  0,3 
1 200 000  ± 11 400  5 800  0,5  
600 000  ± 7 800  4 000  0,7  
300 000  ± 6 100  3 100  1,0  
100 000  ± 3 300  1 700  1,7  
50 000  ± 2 500  1 300  2,6  
10 000  ± 800  400  4,0  
Unemployed  230 000  ± 7 100  3 600  1,6 
120 000  ± 5 700  2 900  2,4  
90 000  ± 4 500  2 300  2,6  
60 000  ± 3 500  1 800  3,0  
30 000  ± 2 400  1 200  4,0  
20 000  ± 2 000  1 000  5,0  
10 000  ± 1 600  800  8,0 
1) The data can be used as indicative estimates of the accuracy of comparable numbers of the employed and unemployed by gender, are and region.
Statistical description of the reliability of estimation
The estimation procedure of the Labour Force Survey is based on the calibration of weights in which the original sample weights calculated on the basis of the sample design are adjusted with a regression model to get the desired population distributions.
The accuracy of estimates is evaluated on the basis of their standard error. Standard error (the square root of the sample variance) describes how neatly the value of the parameter estimated from the observations is concentrated around the parameter of the population. The magnitude of the standard error is affected by sample design, the number of observations in the relevant population or subgroup, variation due to the distribution of the research variable as well as properties of the mathematical formula.
Key figures of reliability derived from the standard error are the confidence intervals and relative standard error. Confidence interval describes the width of the range in which the real value of the parameter is relative to the estimate calculated from the sample. When calculating the confidence interval, the desired level of risk is fixed. The 5 per cent risk level applied in the Labour Force Survey means that if the samples were drawn again, in 95 cases out of one hundred the real value of the parameter would be within the confidence interval and in 5 cases out of one hundred it would be outside the confidence interval.
Relative standard error (coefficient of variation) is the percentage chare of the standard error of the estimate. Proportioning the standard error to the estimate’s size removes the effect of the scale of the variable. Hence the values of the relative standard error of different variables and the values of the standard error of the same variable in different subgroups are easy to compare with one another.
In the monthly and quarterly data of the Labour Force Survey, the estimator of the standard error is the variance estimator of the generalised regression estimator (GREG). The statistical accuracy of the annual estimates and its evaluation is also affected by the fact that the sample of the Labour Force Survey changes gradually during the year. In consecutive quarters 60 per cent of the respondents are the same. During one year 90 per cent of the interviewees have been interviewed at least twice. The responses given by the same persons in different interviews during the year correlate to one another if the person’s labour market status does not change between interviews. To account for this correlation in variance estimation, the Labour Force Survey uses an approximation of single stage cluster sampling in which a withincluster variance is calculated for persons interviewed several times during the year. Clusters are formed on the basis of interviewee’s age. Withincluster variance is zero it the interviewee’s labour market status does not change during the year between different interviews.
For example, the standard error calculated for annual estimate of the unemployed in a subgroup of 230,000 persons is 3,600 persons and the confidence interval is 230,000 ± 7,100 persons. If the interviews on which the annual estimate is based had all been with different persons, the standard error of the estimate of the unemployed had been 2,300 persons and the confidence interval 230,000 ± 4,500 persons. Interviewing the same persons again in different quarters of the year explains why the difference in the accuracy of the annual and quarterly data of the Labour Force Survey is not as big as could be expected on the basis of the interviews conducted.
4. Timeliness and promptness of published data
The results of the Labour Force Survey are released monthly, quarterly and annually. Quarterly and annual results are the averages of monthly results, i.e. they describe the situation on an "average" week during the survey period. Data on labour input are sums of the results of periods. The released data are final. Only seasonal adjustment slightly alters the latest seasonally adjusted monthly results.
Monthly data are released approximately three weeks from the end of the survey month. Quarterly data are released simultaneously with the last monthly data of each quarter. Quarterly data are statistically more reliable than monthly data and contain more detailed data, inter alia, employment and labour input by industry and more specific regional data. Quarterly deliveries of data are made to the EU, which are used to compile statistics on EU Member States. The most detailed data are released in the annual statistics which is finalised approximately six months from the end of the survey year.
5. Accessibility and transparency/clarity of data
The results of the Labour Force Survey are published in the Labour market series of the Official Statistics of Finland. The key monthly and quarterly results are released on predefined days in the Internet on the home page of the Labour Force Survey http://tilastokeskus.fi/til/tyti/index_en. The links on the home page lead, among other things, to a description of the statistics, concepts and definitions as well as the free of charge tables from the statistical databases of the Labour Force Survey (StatFin). Data are available over the Internet also from Statistics Finland's chargeable time series and regional databases (ASTIKA and ALTIKA).
The annual publication of the labour force statistics contains a description of survey methodology, definitions of key concepts, descriptions of classifications used as well as the survey questionnaire. The tables of the annual publication are available also in electronic form. Statistics on the education of the labour force and occupational structure are published every other year also in the OSF Labour market series. In addition, Labour Force Survey data are published regularly in the Statistical Yearbook of Finland and the Bulletin of Statistics.
More and more data are delivered as special compilations according to customers’ needs. The data of the Labour Force Survey and its ad hoc modules may also be released for research purposes on the basis of an application for licence to use statistical data.
Information service: tyovoimatutkimus@stat.fi and tel. +358 9 1734 2030.
6. Comparability of statistics
A monthly Labour Force Survey has been conducted since 1959. During this time the data content, data collection methods and methodology have been revised on several occasions. A comparable time series of the key data exists since 1989.
In the beginning, the survey with more limited data content was conducted as a postal inquiry. In 1976 the data contents expanded and methodology was modernised. During 1977–1993 the survey consisted of a monthly inquiry and supplementary annual interviews conducted over the telephone. The data collection of the monthly inquiry was changed in 1983 from a postal inquiry to a telephone interview, as a result of which nonresponse dropped from 30 to 4 per cent.
When Finland joined the European Union the Labour Force Survey was harmonised with the European Union Labour Force Survey. In the beginning in the years 19951998 the data for the EU Labour Force Survey were collected as a separate interview survey in MarchMay. The monthly survey was gradually revised to correspond to the EU Labour Force Survey. Several changes took place in 1997. The contents of the monthly survey were extended, data collection became a computerassisted telephone interview (CATI) and concepts and definitions were harmonised to correspond better than before to the EU and ILO guidelines and recommendations. The most recent revision of the definition of an unemployed person was made in May 1998. In April 1999 data contents continued to expand as the monthly survey and the EU Labour Force Survey were combined into a single continuing Labour Force Survey. Since 2003 data contents expanded by a so called household section collected from a sub sample.
Published time series have been corrected retroactively as from 1989 to correspond to the renewed definitions. In the beginning of 2000 a continuing survey week was adopted, earlier the data for each month were collected concerning one survey week. The adoption of the continuing survey week affected working day and working hour data, which made them incomparable with earlier data as from 2000.
7. Coherence and consistency/uniformity
In addition to the Labour Force Survey, Statistics Finland’s statistics related to the labour market include the Job vacancy survey, the Quality of working life survey, statistics on labour disputes, statistics on accidents at work as well as an annual registerbased employment statistics (RES).
Of these the RES provides data on the labour market activities of the population (http://tilastokeskus.fi/til/tyokay/index_en.html). Its data differ from those of the Labour Force Survey due to data collection methods and definitions of the employed and the unemployed. The RES is based on total data derived from the administrative data of different authorities. The RES data on a person’s activities refer mainly to the last week in the year. Data on unemployment is based on the Ministry of Labour’s register of unemployed job seekers. The statistics are finalised in a good 1 ½ years, preliminary data are ready after roughly one year. Since employment statistics are total data, they offer better regional data (also data on municipalities) as well as better data on small population groups, e.g. small industries and occupations than the Labour Force Survey. The concepts of the employment statistics based on administrative registers are not internationally comparable.
Statistics Finland uses the Labour Force Survey data in the compilation of National Accounts. Because of this, among other things, the definitions of the key concepts in the Labour Force Survey such as population, employment, working hours, follow as closely as possible the recommendations of the national accounts (the UN System of National Accounts, SNA, and the European System of Accounts, ESA). The definition of the public sector used in the Labour Force Survey is somewhat different from the sectoral classification of the national accounts. In national accounts, conscripts are classified as employed, according to the ILO recommendation, whereas in the Labour Force Survey, conscripts are regarded as economically inactive.
The results of the Finnish Labour Force Survey published by Eurostat, the Statistical Office of the European Communities, differ from those published in Finland in that conscripts are not included in the Eurostat data. In most EU countries conscripts are not included in the target group of the Labour Force Survey, i.e. the socalled household population. This causes differences especially in the results concerning the 15 to 24yearolds.
The Ministry of Labour also publishes statistics on unemployed job seekers. The Ministry’s data are based on the Labour Exchange register, which describe the last working day of the month. The definition of unemployed applied in the Labour Exchange Statistics is based on legislation and administrative orders which make the statistical data internationally incomparable. In the Labour Exchange Statistics an unemployed person is not expected to seek work as actively as in the Labour Force Survey. There are differences also in the acceptance of students as unemployed.
Source: Labour force survey 2007, May. Statistics Finland
Inquiries: Pekka Tossavainen (09) 1734 3517, Juha Martikainen (09) 1734 3225, Heidi MelasniemiUutela (09) 1734 2523, tyovoimatutkimus@stat.fi
Director in charge: Riitta Harala
Updated 19.6.2007
Official Statistics of Finland (OSF):
Labour force survey [epublication].
ISSN=17987857. May 2007,
Quality Description: Labour force survey
. Helsinki: Statistics Finland [referred: 15.9.2019].
Access method: http://www.stat.fi/til/tyti/2007/05/tyti_2007_05_20070619_laa_001_en.html